Q
qatent
qatent is a self service AI patent drafting product sold by Questel, which acquired the company in March 2024. According to Questel's announcement, qatent began at the INRIA Paris research center and was founded by French patent attorneys and German AI researchers. A user generates a first draft of a patent application from its claims, all at once or section by section, in a format ready for a PCT filing. The product also generates claims with novelty diagnostics, models a draft on an existing patent and describes drawings with machine vision.
Drafting is offered in four languages, among them English, French and Chinese, for patent attorneys and for newcomers to patent drafting. qatent is priced at 200 euros per user a month or 2,000 euros per user a year, excluding tax, with no long term commitment. Questel says qatent runs on its architecture in Sophia-Antipolis, France, with Microsoft Azure as its AI provider, and that models are never improved on customer data. Questel is certified to ISO/IEC 27001 and sells qatent alongside its Orbit search and Equinox IP management software.
Capability grades
All 15 axes, graded from public sources on the date shown. Hover a grade to see what the letter means on that axis.
AI Centrality
How much of the product is actually AI. Whether the machine learning is the mechanism the buyer is paying for or a feature layered onto conventional software, and whether the vendor is specific about which is which.
The AI drafting is the product, and removing the models would leave nothing to subscribe to. The qatent page describes a self service tool that writes the first draft of a patent application from the claims, all at once or section by section. It also generates claims with novelty diagnostics, models a draft on an existing patent, imports an invention disclosure and describes drawings with machine vision. The supporting tools for IPC classes and reference numerals serve the generated draft rather than standing as a product of their own. Questel's acquisition announcement presented qatent as a company whose use of AI broke new ground in the IP sector.
Citation Accuracy and Hallucination Disclosure
Whether the vendor publishes measured accuracy on citations and assertions, grounds output to primary sources, and says plainly what its system does when it does not know. Legal has a documented public record of fabricated citations reaching filed briefs, so an untested claim of accuracy is not evidence.
Errors are acknowledged and never measured. Nothing on the qatent page says how accurate a generated draft or claim set is, how novelty diagnostics are computed or against which prior art, or how a description stays faithful to the claims and drawings. Questel's AI Policy disclaims accuracy and acknowledges the potential for hallucinations. A Questel webinar page of 1 October 2024 says the software enhances speed and accuracy, with no figure behind it. No measure of how often a draft needs correction is published.
Autonomy and Oversight Model
What the system decides on its own, what a lawyer must approve, and whether the vendor documents where the review point sits. A tool that drafts under review and a tool that files without one are different products and different risks.
Review is placed on the user, and no oversight mechanism is described for the drafting. The AI Policy tells clients to review and verify the accuracy and completeness of AI generated outputs before relying on them. A draft can be generated section by section, which allows review as it builds, and the product is described as designed by patent attorneys. Nothing states what the system does without review, where a reviewer must sign off before a draft leaves the tool, or what happens when a generated claim or description is wrong. For the newcomers to patent drafting it is also sold to, that instruction is the only control published.
Operational and Outcome Evidence
Named, dated evidence that the product works in production at real firms or legal departments. Case studies with figures and identified customers count. Unattributed testimonials and launch announcements do not.
No production evidence is published. The qatent page carries no customer names, testimonials, case studies or usage figures, and neither the acquisition release nor the webinar page names a customer. Independent reviews of the product's output have been published, and they are evaluations rather than deployments. No firm that drafts with qatent can be identified from published material, and nothing shows what changed for one.
Privilege and Confidentiality Posture
How client confidences are handled: attorney client privilege and work product treatment, segregation of one client matter from another, whether client data trains any model, and what the vendor commits to in writing rather than in marketing.
Commitments on training, encryption and retention are published, and the agreement that would bind them is not. The Trusted AI page says the customer owns its inputs and outputs. The training commitments on the qatent page, the Trusted AI page and the AI Policy all sit outside any published contract, as do the encryption and retention statements. The AI Policy says the Master Services Agreement and Data Processing Agreement govern this, and neither is published.
Nothing addresses segregation between users or teams in a subscribing firm, or the handling of unpublished invention disclosures as confidential material.
UPL and Professional Responsibility Posture
Whether the vendor is clear that it supplies a tool rather than legal advice, who its audience is, and how it addresses unauthorized practice of law, competence and supervision duties, and jurisdiction limits. ABA Formal Opinion 512 is the reference point. Where the advice line is not the duty a product raises, the axis is read through the nearest professional duty it does raise: judicial conduct rules and the reviewing duty for products sold only to courts, and the duty to bill for time actually spent for products that draft time entries.
A published advice line applies, and the product is also sold to people who are not patent professionals. Article 5 of the AI Policy says the services are not intended to replace or substitute the expertise and judgment of legal professionals, and that clients should seek professional legal advice before relying on AI generated outputs. The qatent page says the product is designed by patent attorneys for patent attorneys and for newcomers, and the self service subscription needs no sales contact.
Nothing addresses an inventor or other newcomer who drafts and files an application without a registered practitioner. Patent office rules on representation, and a practitioner's supervision duties when an assistant drafts with the tool, go unmentioned too.
AI Governance and Bias Disclosure
Published governance over model behavior: who owns it inside the vendor, what is tested before release, and what is disclosed about disparate output across matter types, parties, or populations.
A group AI governance framework applies, without testing results or a named owner for qatent. The AI Policy linked from the qatent page commits Questel to comply with the EU AI Act. Article 6 describes an AI Committee and a dedicated AI taskforce drawing on the legal, information security and data privacy functions, with ongoing staff training on AI ethics and security. Article 4 commits to safeguards against bias and misuse, and the Trusted AI page adds an AI oversight committee.
Nothing published is specific to qatent. There is no evaluation of draft quality, no testing before release, no named person accountable for the drafting models, and nothing on uneven output across drafting languages or technical fields.
AI Safety and Data Stewardship
Retention, deletion, access control, and what happens to prompts and documents after they are processed. Whether the vendor states its subprocessors and its incident practice, or leaves the buyer to assume.
Encryption and access are described for Questel's AI in general, and the rest of stewardship is thin. The Trusted AI page says data is encrypted with AES 256 at rest and TLS 1.2 or better in transit, and that access is limited to authorized employees and contractors bound by confidentiality. Retention is under the customer's control. The Data Privacy Policy, updated May 2026, keeps personal data as long as necessary without a period, and names website marketing and analytics tools rather than processors of customer content.
It describes breach notice to the supervisory authority rather than to customers. No subprocessor list for qatent and no customer facing incident commitment is published.
AI Liability and Recourse
What the vendor stands behind contractually when its output is wrong. Indemnities, caps, carve outs, insurance, and whether any of it is published or only reachable through a negotiated agreement.
An accuracy disclaimer is the only published term, and the agreement itself is not public. Article 5 of Questel's AI Policy says Questel does not guarantee the absolute accuracy of AI generated content, given the potential for errors or hallucinations, and places use of the services under each client's professional responsibility. The Master Services Agreement the policy refers to is not published, and the subscribe link leads to the app sign in without displaying terms.
No indemnity, liability cap, warranty on output or recourse for a defective draft is published. Filing deadlines and claim scope are at stake in a patent application, and the loss on everything the policy disclaims falls on the subscriber.
Practice Systems Integration Depth
How deeply the product reaches into the systems legal work already lives in: document management such as iManage and NetDocuments, Word and Outlook, contract lifecycle management, matter management, e-billing, and court filing systems.
No integration into practice systems is published. The qatent page describes importing an invention disclosure and a self service app at my.qatent.com, and names no connection to Questel's Equinox or Orbit, to a document management system, to Microsoft Word or to a patent office filing system. Questel's acquisition release of 8 March 2024 said qatent's AI would benefit products such as Equinox, without describing an integration. Nothing describes how a finished draft leaves the tool.
Deployment Model and Data Residency
Where the software runs and where the data sits. Multi tenant cloud, single tenant, private deployment, on premises, and whether region of residence is a published option or an enterprise conversation.
Hosting location is stated and tenancy is not. The qatent page says the product runs on Questel's architecture in Sophia-Antipolis, France, and lists servers in Europe and GDPR compliance. Whether the language models run in Azure regions in Europe or elsewhere is not stated. Nor is whether customers share infrastructure or are separated, or whether a firm can choose a region. Questel's Data Privacy Policy covers transfers of personal data outside the European Union through standard contractual clauses, which leaves open where drafts and invention disclosures could travel.
Security Certifications and Trust Center
Independent attestation a buyer can pull without a sales call: SOC 2, ISO 27001, penetration test summaries, a trust center with current reports and named scope rather than a badge image.
ISO/IEC 27001 certification is stated, without scope, date or a route to the report. The qatent page says Questel is certified to ISO/IEC 27001, and the AI Policy describes Questel as an ISO 27001 certified company. No certificate scope, certification body, date or validity period is published. Nothing states whether the qatent infrastructure in Sophia-Antipolis or its Azure model hosting falls within the certified scope, and no SOC 2 report or trust center is published.
Model Supply Chain Disclosure
Which models sit underneath, whose they are, where they run, and whether the vendor commits to telling customers when that changes. A legal buyer inherits every dependency it cannot see.
The AI provider is named, and the models and change notice are not. Microsoft Azure is named as qatent's AI provider. Questel's Trusted AI page, written for its AI generally, names OpenAI through API integrations and open model families such as Mixtral and Llama 2, fine tuned on public patent, trademark and design text or on Questel's own data. It does not say which of these qatent uses. No model version, Azure region or commitment to notify customers of a model change is published.
Commercial Transparency
Whether a buyer can learn what this costs without entering a sales process: published rates, the unit being charged, what sits behind an enterprise tier, and what implementation adds.
The price is published and the purchase is self service. The qatent page sets a per user price by month or by year, and users subscribe when they need to draft and unsubscribe when they do not. The subscribe link leads straight to the app. The unit is the user, and the term is the subscriber's choice of month or year. No implementation fee is mentioned. Not published are any usage limits per user and any volume or firm pricing beyond the per user rate.
Firm and Practice Coverage
Who the product is actually built for. AmLaw, midlaw, small firm and solo, in house departments, government and courts, and which practice areas are supported rather than merely claimed.
The audience and the drafting format are described with substance, and the limits are not. The product addresses patent attorneys and newcomers to patent drafting, produces drafts in a format ready for a PCT filing, and drafts in four languages, among them English, French and Chinese. The material is silent on which technical fields the drafting handles well, and on whether drafts follow the formal requirements of the USPTO, the EPO or national offices beyond PCT format. Whether in house patent departments are served differently from firms is not addressed either.
6 public documents
The public pages on file for qatent, with the recorded signals each one supports and the date it was last read. Open any of them and check the reading against the record.
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Client Data in Training, Primary Law Corpus Provenance, Good Law Verification and 2 more
Read Oct 2, 2026
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Ethical Walls and Matter Segregation, Third Party Request and Subpoena Notice
Read Oct 3, 2026
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questel.com/questel-trusted-ai2 signals
Prompt and Output Retention, Refusal and Uncertainty Behavior
Read Oct 2, 2026
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my.qatent.com/login1 signal
Billing and Fee Posture
Read Oct 2, 2026
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Fabricated Citation Record
Read Oct 2, 2026
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Bar Guidance Alignment
Read Oct 2, 2026
€200 per user/monthEUR, as published, never converted
- qatent costs 200 euros a month per user, or 2,000 euros a year.
- Prices do not include tax.
- You can stop at any time; there is no long contract.
- You sign up yourself without talking to sales.
- Usage limits, if any, are not stated.
A per user subscription bought self service: 200 euros per user a month or 2,000 euros per user a year, excluding tax. There is no long term commitment, and users subscribe and unsubscribe as needed.
Implementation: None stated; the published route is a self service subscription.
Confidentiality and data terms: Not applicable.
Note: Prices exclude tax. The page does not state usage limits per user, volume or firm pricing, or whether all four drafting languages are included.
Legal Signals
What each signal meansA signal records what public sources say on the date shown. It is not a grade and it is not a recommendation. Where a signal reads Not addressed, it means the index did not locate the material in public sources on that date, which is a statement about disclosure rather than about the product.
Client Data in Training
Can material a lawyer puts into this product be used to train a model?
A public policy or trust page states no training on customer content, with no matching term located in the published agreement.
Training on customer data is ruled out in policy at three levels, and no published contract carries it. The qatent page says qatent and its AI provider, Microsoft Azure, ensure that AI models are never improved on customer confidential data. Questel's Trusted AI page says information users submit is not used to train or fine tune its models, and AI Policy Article 3 adds that third party providers undertake not to train on client data. The Master Services Agreement and Data Processing Agreement are not published.
Prompt and Output Retention
How long does the product keep what a lawyer typed, and can that be set to zero?
The customer controls the retention window, by product configuration or by contractual instruction, but zero retention is not stated as available.
The customer controls how long its data is retained, according to Questel's Trusted AI page, which adds that zero data retention applies once a customer leaves and that deleted conversations are removed within 30 days. The page is written for Questel's AI generally and does not name qatent, and no zero retention setting during a subscription is described.
Ethical Walls and Matter Segregation
Does retrieval respect the firm’s ethical walls, or can the model read across them?
Segregation is asserted in public materials with no published detail on how it is enforced.
Role based data access is listed among the security measures in Questel's Data Privacy Policy, and nothing describes how access is separated between users, teams or matters within a subscribing firm. The qatent page says nothing on it.
Third Party Request and Subpoena Notice
If someone subpoenas the vendor for a firm’s data, does the firm hear about it first?
No located term or policy addresses third party requests for customer data.
Personal data may go to authorities under legal obligation with no notice promised, and nothing covers the drafts themselves. Questel's Data Privacy Policy, updated May 2026 and read on 3 October 2026, lists duly authorized public authorities, judicial and control, among recipients of personal data under Questel's legal obligations, with no commitment to tell the customer. That clause covers personal data, not the drafts and invention disclosures held in qatent.
Nothing published addresses a legal demand for that content; the qatent page, the AI Policy and the Trusted AI page were checked on 2 October 2026. The agreements signed with clients are not published, so their notice terms are unknown. Verified 3 October 2026.
Primary Law Corpus Provenance
Where does the law in this product come from, and does the vendor have the right to use it?
No located public material identifies the corpus behind the product’s answers.
The product drafts from the user's own claims and disclosure and generates claims with novelty diagnostics; no located material names what those diagnostics are measured against or the basis on which any source is held. Checked the qatent page and the Trusted AI page on 2 October 2026.
Good Law Verification
Does the product tell you when the authority it just cited has been overruled?
No located public material addresses whether authority is checked for subsequent history.
The product drafts patent applications and does not cite legal authority, so no check of subsequent history applies, and none is described. Checked the qatent page on 2 October 2026.
Refusal and Uncertainty Behavior
What does the product do when the answer is not in the corpus?
No located public material addresses what the product does when it cannot ground an answer.
No located material describes what qatent does when claims or a disclosure are insufficient to support a description. The Trusted AI page states an intention to inform users of uncertainty and give them the means to verify, without describing a behavior in qatent. Checked the qatent page, the AI Policy and the Trusted AI page on 2 October 2026.
Fabricated Citation Record
Does a public court record exist addressing fabricated or hallucinated legal citations in output from this product?
No court order, opinion or disciplinary record addressing fabricated or hallucinated legal citations produced by this product has been located as of the date shown. This is a statement about the public record on that one subject, not a finding about the product, and this signal is not a litigation history.
No court order, opinion or disciplinary record naming qatent as the source of fabricated authority was located as of 2 October 2026. The AI Hallucination Cases database maintained by Damien Charlotin returned no cases for qatent.
Bar Guidance Alignment
Has the vendor engaged in public with the ethics opinions its buyers are bound by?
Public materials refer to professional responsibility in general terms without naming guidance.
The AI Policy's statement that its services do not replace legal professionals is the only professional reference. No patent office practitioner rule, bar guidance or ethics opinion is named on the qatent page, the AI Policy or the Trusted AI page read on 2 October 2026.
Billing and Fee Posture
Does the vendor address what happens to the bill when the work takes an hour instead of six?
Public materials claim time savings without addressing billing or disclosure, and the product sits inside a fee relationship between a lawyer and a client where those savings would change the bill.
The qatent app describes itself as generating quality patents in minutes, not days, and the product is sold to patent attorneys who draft applications for clients. No located material addresses how AI drafted applications are billed or disclosed to a client.
Outside Counsel Guideline Readiness
Can a firm get this vendor through a client’s AI clause without a bespoke negotiation?
A current subprocessor or model provider list is published.
The model providers are named on the qatent page and the Trusted AI page, which covers the model provider part of a client's AI clause. No subprocessor list covering qatent and no published data processing agreement was located.
Court Disclosure Support
If a judge’s standing order requires an AI disclosure, can the product produce one?
No located public material addresses court disclosure or verification certification.
No located material addresses disclosure of AI use to a patent office or court, or a record of which parts of a draft were generated. Checked the qatent page, the AI Policy and the Trusted AI page on 2 October 2026.